Model-Based Dynamic Power Assessment of Lithium-Ion Batteries Considering Different Operating Conditions

• Published in: IEEE transactions on industrial informatics Vol. 10; no. 3; pp. 1948 - 1959
• Main Authors: Xiaosong Hu, Rui Xiong, Egardt, Bo
• Format: Journal Article
• Language: English
• Published: Piscataway IEEE 01.08.2014; The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
• Subjects: Assessments; Battery Management System; Battery management systems; Battery Modeling; Dynamic tests; Dynamics; Electric batteries; Electric vehicles; Electrified Vehicle; Li-Ion Battery; Lithium batteries; Lithium-ion batteries; Load modeling; Mathematical models; Peak Power Assessment; Robustness; Vehicle dynamics; Voltage
• ISSN: 1551-3203; 1941-0050; 1941-0050
• DOI: 10.1109/TII.2013.2284713

This paper is concerned with model-based dynamic peak-power evaluation for LiNMC and LiFePO 4 batteries under different operating conditions. The battery test and our prior study on linear-parameter-varying (LPV) battery modeling are briefly introduced. The peak-power estimation method that incorporates an explicit prediction horizon and design constraints on the battery current, voltage, and SOC are elaborated, and its computational load is analyzed. The discharge and charge peak powers are quantitatively assessed under different dynamic characterization tests, in which a comparison with the conventional PNGV-HPPC method and approaches using the less accurate models is conducted. The robustness of the peak-power estimation approach against varying battery temperatures and aging levels is investigated. The methods to improve the credibility of the peak-power assessment in the context of battery degradation are explored.